Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries.

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized.

Unfavorable social determinants of health are associated with higher burden of financial toxicity among patients with atherosclerotic cardiovascular disease in the US: findings from the National Health Interview Survey.

Background: Atherosclerotic cardiovascular disease (ASCVD) is a major cause of financial toxicity, defined as excess financial strain from healthcare, in the US. Identifying factors that put patients at greatest risk can help inform more targeted and cost-effective interventions. Specific social determinants of health (SDOH) such as income are associated with a higher risk of experiencing financial toxicity from healthcare, however, the associations between more comprehensive measures of cumulative social disadvantage and financial toxicity from healthcare are poorly understood.

Cardiac involvement in hospitalized patients with COVID-19 and its incremental value in outcomes prediction.

Recent reports linked acute COVID-19 infection in hospitalized patients to cardiac abnormalities. Studies have not evaluated presence of abnormal cardiac structure and function before scanning in setting of COVD-19 infection. We sought to examine cardiac abnormalities in consecutive group of patients with acute COVID-19 infection according to the presence or absence of cardiac disease based on review of health records and cardiovascular imaging studies.

Rapid Response to Drive COVID-19 Research in a Learning Health Care System: Rationale and Design of the Houston Methodist COVID-19 Surveillance and Outcomes Registry (CURATOR).

Background: The COVID-19 pandemic has exacerbated the challenges of meaningful health care digitization. The need for rapid yet validated decision-making requires robust data infrastructure. Organizations with a focus on learning health care (LHC) systems tend to adapt better to rapidly evolving data needs.